docs: def _pipeline_cell(args, cell_body):
    """Implements the BigQuery cell magic used to validate, execute or deploy BQ pipelines.
  
     The supported syntax is:
     %%bigquery pipeline [-q|--sql <query identifier>] <other args> <action>
     [<YAML or JSON cell_body or inline SQL>]
  
    Args:
      args: the arguments following '%bigquery pipeline'.
      cell_body: optional contents of the cell interpreted as YAML or JSON.
    Returns:
      The QueryResultsTable
    """
    if args['action'] == 'deploy':
      raise Exception('Deploying a pipeline is not yet supported')
  
    env = {}
    for key, value in datalab.utils.commands.notebook_environment().items():
      if isinstance(value, datalab.bigquery._udf.UDF):
        env[key] = value
  
    query = _get_query_argument(args, cell_body, env)
    if args['verbose']:
      print(query.sql)
    if args['action'] == 'dryrun':
      print(query.sql)
      result = query.execute_dry_run()
      return datalab.bigquery._query_stats.QueryStats(total_bytes=result['totalBytesProcessed'],
                                                      is_cached=result['cacheHit'])
    if args['action'] == 'run':
      return query.execute(args['target'], table_mode=args['mode'], use_cache=not args['nocache'],
                           allow_large_results=args['large'], dialect=args['dialect'],
                           billing_tier=args['billing']).results